covc_encdec.py 文件源码

def analyse_(self, inputs, outputs, idx2word, inputs_unk=None, return_attend=False, name=None, display=False):
        def cut_zero(sample, idx2word, ppp=None, Lmax=None):
            if Lmax is None:
                Lmax = self.config['dec_voc_size']
            if ppp is None:
                if 0 not in sample:
                    return ['{}'.format(idx2word[w].encode('utf-8'))
                            if w < Lmax else '{}'.format(idx2word[inputs[w - Lmax]].encode('utf-8'))
                            for w in sample]

                return ['{}'.format(idx2word[w].encode('utf-8'))
                        if w < Lmax else '{}'.format(idx2word[inputs[w - Lmax]].encode('utf-8'))
                        for w in sample[:sample.index(0)]]
            else:
                if 0 not in sample:
                    return ['{0} ({1:1.1f})'.format(
                            idx2word[w].encode('utf-8'), p)
                            if w < Lmax
                            else '{0} ({1:1.1f})'.format(
                            idx2word[inputs[w - Lmax]].encode('utf-8'), p)
                            for w, p in zip(sample, ppp)]
                idz = sample.index(0)
                return ['{0} ({1:1.1f})'.format(
                        idx2word[w].encode('utf-8'), p)
                        if w < Lmax
                        else '{0} ({1:1.1f})'.format(
                        idx2word[inputs[w - Lmax]].encode('utf-8'), p)
                        for w, p in zip(sample[:idz], ppp[:idz])]

        if inputs_unk is None:
            result, _, ppp = self.generate_(inputs[None, :],
                                            return_attend=return_attend)
        else:
            result, _, ppp = self.generate_(inputs_unk[None, :],
                                            return_attend=return_attend)

        source = '{}'.format(' '.join(cut_zero(inputs.tolist(),  idx2word, Lmax=len(idx2word))))
        target = '{}'.format(' '.join(cut_zero(outputs.tolist(), idx2word, Lmax=len(idx2word))))
        decode = '{}'.format(' '.join(cut_zero(result, idx2word)))

        if display:
            print source
            print target
            print decode

            idz    = result.index(0)
            p1, p2 = [np.asarray(p) for p in zip(*ppp)]
            print p1.shape
            import pylab as plt
            # plt.rc('text', usetex=True)
            # plt.rc('font', family='serif')
            visualize_(plt.subplots(), 1 - p1[:idz, :].T, grid=True, name=name)
            visualize_(plt.subplots(), 1 - p2[:idz, :].T, name=name)

            # visualize_(plt.subplots(), 1 - np.mean(p2[:idz, :], axis=1, keepdims=True).T)
        return target == decode